An innovation agency designs a new programme. The criteria, delivery model, and success metrics are shaped by what current grantees can absorb. Proposals that would require institutional redesign are seen as high-risk. The programme expands, but the system's shape does not change.
Incumbents do not capture ecosystems through malice. They shape them through competence. When an established organisation is genuinely good at what it does, it becomes the natural reference point for what 'good' looks like — in funding criteria, in programme design, in definitions of success.
S6 is structurally invisible to the people most responsible for it. If you are the programme manager who designs funding criteria, you design for what works. What works is what your best current grantees are doing. The criteria are not biased toward incumbents — they reflect genuine evidence about what produces results. The bias is in what counts as evidence.
The same logic applies to governance. Multi-stakeholder boards are typically composed of the organisations that have already demonstrated relevance. Their involvement is legitimate — they have standing, they have expertise, they have skin in the game. But their presence means that the system's direction is being set by people whose incentives are to preserve the conditions that made them relevant.
Established actors, programmes, and trajectories shape future options more strongly than new paths that would require the system to change shape.
Ecosystem Stewardship · Chapter 4Finland illustrates this precisely. Nokia's rise was not a failure of ecosystem governance — it was an extraordinary success. The region accumulated global competitive capability in mobile telecommunications. Talent concentrated, capital flowed, research aligned. The stack that formed — Continuity × Re-proving — was rational at every stage. It produced a world-class industrial system. It also meant that when Nokia's position collapsed, the ecosystem had not been building alternatives. The selection logic that had served the system well became the thing that made adaptation slow.
The stall protects real things. Incumbents provide infrastructure that early-stage actors cannot — procurement relationships, technical standards, talent pipelines, supply chains. A system that destabilised its incumbent base in pursuit of novelty would be trading a working system for an uncertain one. That trade is not obviously correct, and the people responsible for the ecosystem are right to be cautious about it.
What the stall displaces is the system's capacity to let contrast emerge. When all pathways are evaluated against the incumbent template, the contrast between what exists and what might exist is systematically reduced. Novel ventures adapt themselves to the incumbent orbit rather than competing with it. The system can absorb innovation — as long as it does not require the system to change shape.
The leverage move is not to challenge the incumbents. It is to introduce one evaluation process where incumbent-integrated and independent pathways are assessed separately, with their outcomes reported distinctly. Not competitively. Distinctly.
The purpose is not to determine which is better. It is to make visible the difference between what the incumbent orbit produces and what independent pathways produce. In most S6 systems, this comparison has never been made explicit — because making it explicit would force a question about whether the criteria are calibrated to the system's future or its present.
S6 has moderate observability. The presence of incumbent-oriented programme design is visible in funding criteria and governance composition. The displacement claim — that this prevents novelty from reshaping the system — requires evidence that alternative trajectories are systematically disadvantaged, which demands access to rejection data or comparative programme outcomes that are rarely public. Confidence increases when multiple consecutive funding cycles show the same organisations consistently advantaged, and when proposals from new entrants are documented as high-risk without clear technical justification.
The diagnostic identifies which stalls are operating in your cluster — and which stacks they form. That is where intervention design begins.
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